Your browser doesn't support javascript.
Quality of death certificates completion for COVID-19 cases in the southeast of Iran: A cross-sectional study.
Alipour, Jahanpour; Karimi, Afsaneh; Miri-Aliabad, Ghasem; Baloochzahei-Shahbakhsh, Farzaneh; Payandeh, Abolfazl; Sharifian, Roxana.
  • Alipour J; Health Promotion Research Center Zahedan University of Medical Sciences Zahedan Iran.
  • Karimi A; Department of Health Information Technology, School of paramedical Zahedan University of Medical Sciences Zahedan Iran.
  • Miri-Aliabad G; Department of Health Information Technology, School of paramedical Zahedan University of Medical Sciences Zahedan Iran.
  • Baloochzahei-Shahbakhsh F; Pregnancy Health Research Center Zahedan University of Medical Sciences Zahedan Iran.
  • Payandeh A; Children and Adolescent Health Research Center Zahedan University of Medical Sciences Zahedan Iran.
  • Sharifian R; Treatment Affairs Zahedan University of Medical Sciences Zahedan Iran.
Health Sci Rep ; 5(5): e802, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2013525
ABSTRACT
Background and

Aim:

Death certificate (DC) data provides a basis for public health policies and statistics and contributes to the evaluation of a pandemic's evolution. This study aimed to evaluate the quality of the COVID-19-related DC completion.

Methods:

A descriptive-analytical study was conducted to review a total of 339 medical records and DCs issued for COVID-19 cases from February 20 to September 21, 2020. A univariate analysis (χ 2 as an unadjusted analysis) was performed, and multiple logistic regression models (odd ratio [OR] and 95% confidence interval [CI] as adjusted analyses) were used to evaluate the associations between variables.

Results:

Errors in DCs were classified as major and minor. All of the 339 examined DCs were erroneous; more than half of DCs (57.8%) had at least one major error; all of them had at least one minor error. Improper sequencing (49.3%), unacceptable underlying causes of death (UCOD) (33.3%), recording more than one cause per line (20.1%), listing general conditions instead of specific terms (11.2%), illegible handwriting (8.3%), competing causes (6.2%), and mechanisms (3.8%) were most common major errors, respectively. Absence of time interval (100%), listing mechanism allying with UCOD (51.6%), using abbreviations (45.4%), missing major comorbidities (16.5%), and listing major comorbidities in part I (16.5%) were most common minor errors, respectively.

Conclusion:

The rate of both major and minor errors was high. Using automated tools for recording and selecting death cause(s), promoting certifiers' skills on DC completion, and applying quality control mechanisms in DC documentation can improve death data and statistics.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Randomized controlled trials Language: English Journal: Health Sci Rep Year: 2022 Document Type: Article

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Randomized controlled trials Language: English Journal: Health Sci Rep Year: 2022 Document Type: Article